In the recent past, light microscopic imaging methods have been developed with which, based on a sequential, stochastic localization of individual markers, in particular fluorescence molecules, sample structures can be imaged that are smaller than the diffraction-dependent resolution limit of conventional light microscopes. Such methods are, for example, described in WO 2006/127692 A2; DE 10 2006 021 317 B3; WO 2007/128434 A1, U.S. 2009/0134342 A1; DE 10 2008 024 568 A1; “Sub-diffraction-limit imaging by stochastic optical reconstruction microscopy (STORM)”, Nature Methods 3, 793-796 (2006), M. J. Rust, M. Bates, X. Zhuang; “Resolution of Lambda/10 in fluorescence microscopy using fast single molecule photo-switching”, Geisler C. et al, Appl. Phys. A, 88, 223-226 (2007). This new branch of microscopy is also referred to as localization microscopy. The applied methods are known in the literature, for example, under the designations (F)PALM ((Fluorescence) Photoactivation Localization Microscopy), PALMIRA (PALM with Independently Running Acquisition), GSD(IM) (Ground State Depletion Individual Molecule return) Microscopy) or (F)STORM ((Fluorescence) Stochastic Optical Reconstruction Microscopy).
The new methods have in common that the sample structures to be imaged are prepared with markers that have two distinguishable states, namely a “bright” state and a “dark” state. When, for example, fluorescent dyes are used as markers, then the bright state is a state in which they are able to fluoresce and the dark state is a state in which they are not able to fluoresce. For imaging sample structures with a resolution that is higher than the conventional resolution limit of the imaging optical system, a small subset of the markers is repeatedly brought into the bright state. In the following, this subset is referred to as active subset. In this connection, the density of the markers forming the “active” subset is to be chosen such that the average distance of adjacent markers in the bright state and thus in the state in which they can be imaged by a light microscope is greater than the resolution limit of the imaging optical system. The markers forming the active subset are imaged onto a spatially resolving arrangement of sensor elements so that of each marker a light distribution in the form of a light spot is detected whose size is determined by the resolution limit of the optical system.
The present invention relates generally to microscopic imaging. When the density of the markers contained in the active subset is so low that the average distance of the markers, as explained above, exceeds a minimum distance predetermined by the resolution limit of the light microscopic imaging, then a desired activation state is present. This activation state guarantees that each light spot detected by the sensor element arrangement originates from exactly one activated marker.
The above-explained method is illustrated in FIG. 1. In the left-hand side of FIG. 1, a sequence of raw data single frames is illustrated, which are numbered with 1, . . . , N. Each of the light spots imaged in these raw data single frames originates from an active marker subset that is in the desired activation state, i.e. its marker density is so low that it is guaranteed that the average distance of the markers is greater than the minimum distance predetermined by the resolution limit of the light microscopic imaging.
In the upper right-hand part of FIG. 1, a total image is illustrated which results from the superimposition of raw data single frames 1, . . . , N. This total image has a spread-out, spatially non-resolved light distribution which does not reproduce the sample structure to be imaged in detail.
In the lower right-hand part of FIG. 1, a total image is illustrated which results from the superimposition of centroids of the light distributions determined from the raw data single frames. This total image has a much higher resolution so that the sample structure can be well identified in detail—in the present example with its three concentric circular rings.
For quantifying the localization precision which is to be achieved in the above-explained method, reference is made to FIG. 2 in which the situation shown in FIG. 1 is again illustrated merely schematically. In the upper part of FIG. 2, a sequence of raw data single frames is shown. The sample structure to be imaged, which is comprised of concentric circular rings, is illustrated in broken lines in FIG. 2 and is identified with the reference sign 2.
The individual markers of the active subset generate light distributions 4 whose size is determined by the resolution capability of the imaging optical system and is identified with ΔxAbb in FIG. 2. As schematically illustrated in FIG. 2, the markers have an average distance to one another that is smaller than the size ΔxAbb so that the light distributions 4 do not overlap.
In the lower part of FIG. 2, light distributions 6 are shown which result from the light distributions 4 obtained by the centroid determination. The achievable localization precision is given by the size ΔxSP of the light distributions 6. For the localization precision ΔxSP the following applies:
  Δ  ⁢          ⁢      x    SP    ⁢  α  ⁢            Δ      ⁢                          ⁢              x        Abb                    n      
wherein n denotes the number of photons detected per light distribution 4. The localization precision ΔxSP is typically in a range of about 10 to 50 nm.
Prior to the capturing of a raw data single frame, the above-explained activation state is to be established. From which initial state this activation state is to be established, differs from method to method. Basically, two methods have to be distinguished, namely a method referred to as “bottom-up” method and a method referred to as “top-down” method. In the bottom-up method, at first all markers are in their dark state. The generation of the active marker subset as required for the high-resolution localization is achieved by an appropriate activation, e.g. by irradiation of activation light. This is for example the case for the (F)PALM method. In contrast thereto, in the top-down method at first all markers are in their bright state, i.e. their state in which they can be imaged by a light microscope. For generating the active marker subset, then most of the markers are brought into their dark state, again for example by irradiation of light. Here, the markers can be so-called “switchable” markers, e.g. switchable proteins. Likewise, these markers can, for example, be specific conventional fluorescent dyes which change into long-lived dark states, e.g. triplet states, when irradiated with excitation light (and thus are non-switchable markers in the true sense). For example, the GSD(IM) methods make use thereof.
Both in the bottom-up method and in the top-down method, it is relatively difficult to reproducibly establish the predetermined activation state which only makes the high resolution localization of the individual markers possible. In particular, it is not possible up to now to determine in an easy manner whether this predetermined activation state is present or not. Thus, it often occurs that too many of the markers are in their bright state so that the light distributions generated by the markers are not spatially separated from one another in the raw data single frames. This makes the light microscopic imaging of the sample structure more difficult, in particular the decision when the actual measuring can be started, i.e. when actually only so few markers are still in their bright state that the light distributions generated by the markers have, with a sufficiently high probability, a spatial distribution which makes a separate detection of the light distributions possible.